Nursing Education: What Fits Best in a Changing World of Education Gogies?
Bibliographic record
Abstract
Nursing education has roots in religious organizations, and apprenticeship approaches to ‘training’ nurses. Over time nursing education has moved to universities; yet retaining the critical practice nature of nursing. As a practice profession, nursing educators have to face the realities of ensuring that knowledge, skills, and values are taught in order for graduates to meet the entry to practice competencies. As graduates, nurses must also have the capacity to assess their knowledge gaps and be self-directed in filling those gaps so that they are providing evidence-based practice to those in their care. Educators must facilitate learning within best education practice, often identified as learner-centred approaches. In this discussion paper, we examine how nursing education has evolved, we critically examine the broader concepts of pedagogy, andragogy, heutagogy and academagogy, and discuss how these fit within learner-centred approaches to nursing education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.029 | 0.040 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".